A financial services company runs its production transactional database in Oracle on-premises. They are migrating to Cloud SQL for PostgreSQL and need to keep the two systems in sync continuously during a multi-week cutover window. The source database must remain fully operational, and the team wants to minimize manual intervention. Which service should be used to keep the databases synchronized?

Datastream for continuous change data capture from Oracle to Cloud SQL for PostgreSQL.

Database Migration Service for a one-time continuous migration job.

Cloud Scheduler with Cloud Functions to run periodic SQL queries against Oracle and insert changes into Cloud SQL.

BigQuery Data Transfer Service to schedule nightly batch loads from Oracle.

A large enterprise is migrating its data platform to Google Cloud. The current state includes a 20-node on-premises Hadoop cluster running Hive, a legacy Oracle data warehouse, and several undocumented Python scripts that move data between them. The business has a hard deadline of 9 months and a limited budget. The data engineering team is small and has no prior Google Cloud experience. The compliance team requires that all data processing must remain within the United States. Which migration approach best balances the constraints?

Use Transfer Appliance to ship all data to Cloud Storage and then use Datastream to load it into BigQuery.

Perform a phased migration: first lift-and-shift the Hadoop cluster to Dataproc, then migrate the Oracle warehouse to Cloud SQL, and finally re-architect the Python scripts to use Cloud Composer.

Migrate only the Oracle warehouse to BigQuery and leave the Hadoop cluster on-premises.

Re-architect everything at once into a serverless data platform using BigQuery, Dataflow, and Cloud Functions.

A company is migrating 50 TB of data from an on-premises data center to Google Cloud. They have a 100 Mbps internet connection and a 30-day migration window. The data is not latency-sensitive, but the migration must be secure. The company also has a small remote office that needs to access the data in Google Cloud after migration. What is the most appropriate connectivity and transfer approach?

Order Dedicated Interconnect for the initial data transfer and for the remote office access.

Use Storage Transfer Service from an HTTP source and Cloud NAT for the remote office.

Use `gsutil rsync` over the public internet for the initial load and rely on IAM for security.

Use Transfer Appliance for the initial 50 TB load and set up Cloud VPN for the remote office to access Google Cloud securely.

A data engineer is creating a detailed plan that addresses gaps in people, processes, and technology between the current and desired states. Which activity is this?

Migration planning and gap analysis

Google CloudProfessional Data Engineer

Domain 1Objective 4

1.4 Designing Data Migrations PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 4)

Part of the Designing data processing systems domain, which accounts for ~22% of the PROFESSIONAL-DATA-ENGINEER exam. Google Cloud does not publish an official question count, but from its 120-minute exam (~50–80 total, ~11–18 in this domain), expect 3–5 from this objective — we provide 38 practice questions to prepare you well beyond it. (estimate)

38questions here

8free pages

12concepts

~22%of the exam

Questions 16–20

16foundation · easy
A data engineer needs to replicate changes from a PostgreSQL database to BigQuery in near-real-time. Which Google Cloud service is designed for this?
Select an answer first
17application · medium
A financial services company runs its production transactional database in Oracle on-premises. They are migrating to Cloud SQL for PostgreSQL and need to keep the two systems in sync continuously during a multi-week cutover window. The source database must remain fully operational, and the team wants to minimize manual intervention. Which service should be used to keep the databases synchronized?
Select an answer first
18expert · hard
A large enterprise is migrating its data platform to Google Cloud. The current state includes a 20-node on-premises Hadoop cluster running Hive, a legacy Oracle data warehouse, and several undocumented Python scripts that move data between them. The business has a hard deadline of 9 months and a limited budget. The data engineering team is small and has no prior Google Cloud experience. The compliance team requires that all data processing must remain within the United States. Which migration approach best balances the constraints?
Select an answer first
19application · medium
A company is migrating 50 TB of data from an on-premises data center to Google Cloud. They have a 100 Mbps internet connection and a 30-day migration window. The data is not latency-sensitive, but the migration must be secure. The company also has a small remote office that needs to access the data in Google Cloud after migration. What is the most appropriate connectivity and transfer approach?
Select an answer first
20foundation · easy
A data engineer is creating a detailed plan that addresses gaps in people, processes, and technology between the current and desired states. Which activity is this?
Select an answer first

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1.4 Designing Data Migrations PROFESSIONAL-DATA-ENGINEER Practice Questions (Page 4)

Questions 16–20

A data engineer needs to replicate changes from a PostgreSQL database to BigQuery in near-real-time. Which Google Cloud service is designed for this?

A data engineer is creating a detailed plan that addresses gaps in people, processes, and technology between the current and desired states. Which activity is this?

Keep studying — Designing data processing systems